Agrosatpk

An AI & satellite-powered Precision Agriculture platform that diagnoses crop diseases, provides Urdu voice guidance, and tracks real-time field soil and weather telemetry for farmers.

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🌾 Inspiration

In developing regions like Pakistan, rural farmers face massive crop losses due to undetected plant diseases and unpredictable weather patterns. Furthermore, many small-scale farmers have low literacy rates and struggle to navigate complex digital dashboards or technical reports. We were inspired to bridge this gap by combining cutting-edge AI diagnostic tools with real-time satellite telemetry—delivered through a voice-guided, bilingual interface that any farmer can easily understand.

🚀 What It Does

AgroSat Pakistan is an end-to-end precision agriculture platform designed for field analytics and immediate crop health assessment:

  • 🍃 Leaf Disease Diagnostics: Scans crop leaf images to instantly detect plant diseases with high accuracy using deep learning computer vision datasets.
  • 🎙️ Voice Assistant (Urdu Audio): Automatically reads out disease diagnosis and step-by-step treatment/spray recommendations in local Urdu speech.
  • 🛰️ Field Telemetry Analytics: Integrates satellite and weather data to track real-time Soil Moisture, Soil Temperature, Ambient Temperature, and Precipitation (Rainfall).
  • 🗺️ Dynamic Field Map: Allows farmers to pinpoint their exact farm location to receive localized micro-climate updates.

🛠️ How We Built It

  • Frontend UI: Built a responsive, high-contrast dark UI using HTML5, CSS3, and JavaScript designed for high visibility in outdoor field conditions.
  • Computer Vision AI: Powered by the PlantVillage dataset (trained to classify 38 plant disease classes with 95%+ accuracy).
  • Voice & Accessibility: Leveraged the Web Speech API and Text-to-Speech engines for localized Urdu voice output.
  • Satellite & GIS Integration: Used Leaflet.js for interactive field mapping along with open-source telemetry data pipelines.

🧗 Challenges We Ran Into

  • Accessibility for Non-Literate Users: Designing an intuitive interface where complex scientific telemetry (soil moisture %, temperature metrics) is translated into actionable local audio instructions.
  • Local Language TTS Syncing: Calibrating audio feedback triggers to smoothly speak Urdu treatment advice right after leaf diagnostic results are processed.

💡 What We Learned

  • How crucial localized AI solutions are for agriculture and real-world impact.
  • How to merge satellite telemetry API streams with client-side AI inferencing for an instant, seamlessly responsive web app.

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